Email this article Penentuan Kelayakan Kredit Dengan Algoritma Naïve Bayes Classifier: Studi Kasus Bank Mayapada Mitra Usaha Cabang PGC
Abstract
In analyzing a credit sometimes a less accurate credit officer in credit analysis, so that it can lead to increased bad debts. Classification data mining algorithms are widely used to determine the credit worthiness of one Naive Bayes classifier, NBC superior in increasing the value of high accuracy but weak in the selection of attributes. After testing Naive Bayes classifier algorithm the results obtained is Naive Bayes classifier algorithm produces an accuracy of 89.33% and AUC values for 0.955.
Keyword: Credit Analysis, Naive Bayes ClassifierAlgorithm
References
Xhemali, D., Hinde, C.J. and Stone. R.G. (2009). Naive Bayes vs Decision Trees vs. Neural Network in the Classification of Training Web Pages. IJCSI International Journal of Computer Science Issues, 4(1). Pp. 16-23.
Yap, Bee W., Ong, Seng H., and Husain. N.H.M, (2011). Using Data Mining to Improve Assessment of Credit Worthiness via Credit Scoring Models. Expert System with Applications, 38(2011) 13274-13283
Undang-Undang Republik Indonesia Nomor 10 Tahun 1998 tentang perubahan atas Undang-Undang Nomor 7 Tahun 1992 tentang perbankan.
Larose, D.T.( 2005). Discovering Knowledge in Data. Canada: Wiley-Interscience.
Larose, D.T.( 2005). Discovering Knowledge in Data. Canada: Wiley-Interscience.
Xhemali, D., Hinde, C.J. and Stone. R.G. (2009). Naive Bayes vs Decision Trees vs. Neural Network in the Classification of Training Web Pages. IJCSI International Journal of Computer Science Issues, 4(1). Pp. 16-23.
Han, J., and Kamber, M. (2006). Data Mining Concept and Techniques. San Francisco: Diane Cerra.
Bramer, Max. (2007). Principles of Data Mining. London: Springer. ISBN-10: 1-84628-765-0, ISBN-13: 978-1-84628-765-7
Gorunescu, Florin. (2011). Data Mining Concepts, Models and Techniques. Intelligent System Reference Library, Vol 12, ISBN 978-3-642-19721-5.
Han, J., and Kamber, M. (2006). Data Mining Concept and Techniques. San Francisco: Diane Cerra.
Vercellis, Carlo. (2009). Business Intelligence: Data Mining and Optimization for Decision Making. United Kingdom: John Willey & Son
DOI: https://doi.org/10.31294/jtk.v3i1.1337
Copyright (c) 1969 Nia Nuraeni
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
ISSN: 2442-2436 (print), and 2550-0120
